CN111427878B - Data monitoring alarm method, device, server and storage medium - Google Patents
Data monitoring alarm method, device, server and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a data monitoring alarm method, a device, a server and a storage medium. The data monitoring and alarming method comprises the following steps: acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information. The effect of timely monitoring and alarming the data is achieved.
Description
Technical Field
The embodiment of the invention relates to the technical field of data monitoring, in particular to a data monitoring alarm method, a device, a server and a storage medium.
Background
With the rapid development of big data, more and more enterprises use the characteristic data of users to recommend commodities to the users.
At present, when recommending goods, a common method is to query feature data of a user, and then input the feature data into a pre-trained model so as to predict goods liked by the user. Therefore, the user characteristic data is very important for the effect of recommendation. If an abnormality occurs, the overall recommendation effect is affected.
However, at present, the characteristic data of the user is not monitored, and the problem is examined only when the effect of daily statistical recommendation is not good, so that the problem is found to be seriously lagged.
Disclosure of Invention
The embodiment of the invention provides a data monitoring and alarming method, a device, a server and a storage medium, so as to realize timely monitoring and alarming of data.
In a first aspect, an embodiment of the present invention provides a data monitoring alarm method, including:
acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information;
determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
judging whether the monitoring parameters meet preset parameters or not;
and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information.
Optionally, the acquiring the feature data set of the user includes:
monitoring a message queue, wherein the message queue is used for receiving the characteristic data set from a recommendation system;
the feature data set is extracted from the message queue when the message queue update is monitored.
Optionally, the determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
extracting initial parameters corresponding to the characteristic information from the characteristic data set, so as to determine monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information.
Optionally, the feature information is multiple, and determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
determining a monitoring parameter corresponding to each piece of characteristic information according to the initial parameter of each piece of characteristic information;
judging whether the monitoring parameters meet preset parameters or not, and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information comprises the following steps:
judging whether the monitoring parameters corresponding to each piece of characteristic information meet the corresponding preset parameters or not;
determining the characteristic information that the monitoring parameters do not meet the corresponding preset parameters as target characteristic information;
and carrying out alarm prompt on the target characteristic information.
Optionally, the determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
storing initial parameters corresponding to the characteristic information into a distributed document database;
judging whether the current time reaches a first preset time or not;
when the current time reaches the first preset time, calling initial parameters corresponding to the characteristic information from the distributed document database;
and calculating initial parameters corresponding to the characteristic information to determine monitoring parameters corresponding to the characteristic information.
Optionally, the monitoring parameters include average response time consumption, null value duty ratio and/or request exception duty ratio, the judging whether the monitoring parameters meet preset parameters or not, and when the monitoring parameters do not meet the preset parameters, sending an alarm prompt of feature information exception includes:
judging whether the average response time consumption, the null value duty ratio and/or the request abnormal duty ratio meet preset parameters corresponding to the average response time consumption, the null value duty ratio and/or the request abnormal duty ratio or not;
and when the average response time consumption, the null value duty ratio and/or the request abnormality duty ratio do not meet the preset parameters corresponding to the average response time consumption, the null value duty ratio and/or the request abnormality duty ratio, sending out an alarm prompt of the characteristic information abnormality.
Optionally, the determining whether the monitored parameter meets a preset parameter includes:
calling a preset configuration table from a preset database, wherein the preset configuration table carries the preset parameters;
and judging whether the monitoring parameters meet preset parameters of the preset configuration table or not.
In a second aspect, an embodiment of the present invention provides a data monitoring alarm device, including:
the device comprises a feature data set acquisition module, a feature data set acquisition module and a feature data processing module, wherein the feature data set is used for acquiring a feature data set of a user, and comprises feature information of the user and initial parameters corresponding to the feature information;
the monitoring parameter determining module is used for determining the monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
the judging module is used for judging whether the monitoring parameters meet preset parameters or not;
and the alarm prompt module is used for sending out alarm prompts with abnormal characteristic information when the monitoring parameters do not meet the preset parameters.
In a third aspect, an embodiment of the present invention provides a server, including:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data monitoring alert method as described in any embodiment of the present invention.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a data monitoring alarm method according to any embodiment of the present invention.
According to the embodiment of the invention, the characteristic data set of the user is obtained, wherein the characteristic data set comprises the characteristic information of the user and the initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; when the monitoring parameters do not meet the preset parameters, an alarm prompt of abnormal characteristic information is sent, the problem that the characteristic data of a user are not monitored is solved, and the effect of monitoring and alarming the data in time is found only when the effect of daily statistics recommendation is not good.
Drawings
FIG. 1 is a flow chart of a data monitoring and alarming method according to an embodiment of the present invention;
fig. 2 is a flow chart of a data monitoring and alarming method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a data monitoring alarm device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a server according to a fourth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart depicts steps as a sequential process, many of the steps may be implemented in parallel, concurrently, or with other steps. Furthermore, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Furthermore, the terms "first," "second," and the like, may be used herein to describe various directions, acts, steps, or elements, etc., but these directions, acts, steps, or elements are not limited by these terms. These terms are only used to distinguish one direction, action, step or element from another direction, action, step or element. For example, the first information may be referred to as second information, and similarly, the second information may be referred to as first information, without departing from the scope of the present application. Both the first information and the second information are information, but they are not the same information. The terms "first," "second," and the like, are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
Example 1
Fig. 1 is a schematic flow chart of a data monitoring and alarming method provided in an embodiment of the present invention, which is applicable to a scenario of monitoring and alarming feature data for commodity recommendation, where the method may be performed by a data monitoring and alarming device, and the device may be implemented in a software and/or hardware manner and may be integrated on a server.
As shown in fig. 1, a data monitoring and alarming method provided in an embodiment of the present invention includes:
s110, acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information.
Wherein the feature data set refers to a set comprising feature information for making a recommendation of a commodity to a user. The feature information refers to information related to user characteristics. In this embodiment, the feature information is information that has a large influence on the recommendation effect. For example, the characteristic information may be information of sex, occupation, hobbies, income, etc., and is not particularly limited herein. The initial parameters refer to parameters related to the feature information. Alternatively, the initial parameters may be parameters such as time consuming response to obtain the feature information, whether the obtained feature information is empty, whether the request to obtain the feature information fails, and the like, which are not particularly limited herein. In this embodiment, the data set may include the feature information of the same user and the initial parameters of the feature information, or may be the same feature information of different users and multiple initial parameters of the same feature information, which is not limited herein. For example, the feature data set includes response times for acquiring feature information of user a; for another example, the feature data set includes response times corresponding to the same feature information of user B and user C, respectively.
In an alternative embodiment, acquiring the feature data set of the user comprises:
monitoring a message queue, wherein the message queue is used for receiving the characteristic data set from a recommendation system; the feature data set is extracted from the message queue when the message queue update is monitored.
In this embodiment, the message queue is a container that holds the feature data set during transmission of the message. Specifically, the message queue receives a feature data set from the recommender system. The recommending system is used for recommending commodities to the user according to the characteristic information in the characteristic data set of the user, such as recommending loan products or recommending physical products. Therefore, when the feature information in the feature data set is abnormal, the recommended effect of the recommended product is not good. When the message queue is updated, the feature data set sent by the recommendation system is indicated, and the feature data set is extracted from the message queue.
S120, determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information.
The monitoring parameters are used for judging whether the acquisition of the characteristic information is abnormal or not. Specifically, when the feature data set includes feature information of the same user and an initial parameter of the feature information, the initial parameter may be used as a monitoring parameter, for example, time consumed for acquiring the feature information of the user a, whether the feature information of the user a is empty, and whether a request for acquiring the feature information of the user a is successful. When the feature data set includes the same feature information of different users and a plurality of initial parameters of the same feature information, average response time can be obtained by averaging response time of the feature data sets of the obtained different users, statistics is performed on empty value duty ratio of the same feature information of the different users, statistics is performed on request anomaly duty ratio of the obtained user feature data set with abnormal request, namely, average response time, empty value duty ratio and request anomaly duty ratio of the monitoring parameters. The null value duty ratio refers to the ratio of the number of nulls returned for the same characteristic information for different users to the number of all the same characteristic information. The request exception duty cycle refers to the ratio of the number of failed requests to acquire the user's feature data set to the total number of requests to acquire the feature data set.
In an optional embodiment, determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
storing initial parameters corresponding to the characteristic information into a distributed document database; judging whether the current time reaches a first preset time or not; when the current time reaches the first preset time, calling initial parameters corresponding to the characteristic information from the distributed document database; and calculating initial parameters corresponding to the characteristic information to determine monitoring parameters corresponding to the characteristic information.
The embodiment is suitable for a scene of monitoring and alarming according to a plurality of initial parameters corresponding to the same characteristic information of different users. In this embodiment, each field in the distributed document database may be indexed, and the data for each field may be searched. The first preset time refers to a time for judging whether to call the initial parameters to perform calculation of the monitoring parameters. Alternatively, the first preset time may be obtained by adding a preset time period to the time of calculating the monitoring parameter last time, for example, adding five minutes to the time of calculating the monitoring parameter last time. In this embodiment, specifically, the feature information of different users and initial parameters corresponding to the feature information are continuously acquired and stored in the distributed document database. And if the current time reaches the first preset time, calling all initial parameters of the characteristic information in the preset time period, and calculating the initial parameters corresponding to the characteristic information to determine the monitoring parameters corresponding to the characteristic information. In this embodiment, the monitoring statistics are performed once every preset time period, so that the feature information can be monitored in time.
In an optional embodiment, determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
extracting initial parameters corresponding to the characteristic information from the characteristic data set, so as to determine monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information.
In this embodiment, specifically, the feature data set carries initial parameters corresponding to the feature information, and then the initial parameters corresponding to the feature information are directly extracted from the feature data set, so that monitoring parameters corresponding to the feature information are determined according to the initial parameters corresponding to the feature parameters.
S130, judging whether the monitoring parameters meet preset parameters or not.
The preset parameters are parameters for judging whether abnormal alarm prompt is needed for the characteristic information. For example, when the monitored parameters include average response time, duty cycle, and request exception duty cycle, then the preset parameters include preset standard time, preset duty cycle, and preset exception duty cycle.
In an alternative embodiment, determining whether the monitored parameter meets a preset parameter includes:
calling a preset configuration table from a preset database, wherein the preset configuration table carries the preset parameters; and judging whether the monitoring parameters meet preset parameters of the preset configuration table or not.
In this embodiment, the preset configuration table may configure preset parameters as required. For example, when the preset parameters need to be updated, the preset configuration table is modified and updated to the preset database, so that monitoring and alarming are performed according to the updated preset configuration table. Specifically, when it is required to determine whether the monitoring parameter meets the preset parameter, the preset configuration table is called from the preset database, so as to determine whether the monitoring parameter meets the preset parameter of the preset table, and determine whether to carry out alarm prompt on the feature information.
And S140, when the monitoring parameters do not meet the preset parameters, sending out alarm prompt of abnormal characteristic information.
In the step, when the monitoring parameters corresponding to the characteristic information do not meet the preset parameters, an alarm prompt of the characteristic information is sent out. For example, when the monitoring parameter corresponding to the age characteristic information of the user does not meet the preset parameter, an alarm prompt of the age is sent out to prompt that the age characteristic information is abnormal. For example, when the monitoring parameters include average response time consumption, duty ratio and request exception duty ratio, and the preset parameters include preset standard time consumption, preset duty ratio and preset exception duty ratio, if the average response time consumption is greater than the preset labeling time consumption, the preset duty ratio is greater than the preset duty ratio and the request exception duty ratio is greater than the preset exception duty ratio, the monitoring parameters belonging to the step do not meet the preset parameters; any one or more alarm prompts which are not satisfied and send out characteristic information abnormality can be adopted, and the method is not limited in the aspect. The preset standard time consumption refers to preset parameters corresponding to the average response time consumption. The preset duty ratio refers to a preset parameter corresponding to the duty ratio. The preset abnormal duty ratio refers to a preset parameter corresponding to the request abnormal duty ratio. Alternatively, the mail may be sent to a corresponding mailbox for alerting, etc. by associating with the mailbox system, which is not limited herein. According to the embodiment, the characteristic information is warned, so that the occurrence of abnormality of the characteristic information can be timely determined, and related personnel are informed to conduct investigation timely.
According to the technical scheme, the characteristic data set of the user is obtained, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information. By judging the monitoring parameters of the characteristic information, the problem investigation is avoided when the recommended effect is not good, and the monitoring parameters of the characteristic information can be timely judged to determine whether to alarm or not, so that the technical effect of timely monitoring and alarming the data is achieved.
Example two
Fig. 2 is a flow chart of a data monitoring alarm method according to a second embodiment of the present invention. The embodiment is further refined in the technical scheme, and is suitable for scenes of alarming and prompting a plurality of feature information. The method may be performed by a data monitoring and alerting device, which may be implemented in software and/or hardware and may be integrated on a server.
As shown in fig. 2, the data monitoring and alarming method provided in the second embodiment of the present invention includes:
s210, acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information, and the characteristic information is a plurality of pieces.
In this embodiment, the feature information is plural in detail.
S220, determining monitoring parameters corresponding to each piece of characteristic information according to the initial parameters of each piece of characteristic information.
In this step, each feature information corresponds to a separate one of the monitored parameters. For example, when the characteristic information is occupational, the corresponding preset duty ratio is 3%; when the characteristic information is sex, the corresponding preset duty ratio is 20%, and corresponding monitoring parameters can be set for different characteristic information according to the need, which is not limited herein.
S230, judging whether the monitoring parameters corresponding to each piece of characteristic information meet the corresponding preset parameters.
In the step, the monitoring parameters corresponding to each feature information are subjected to independent corresponding preset parameter judgment. Optionally, the corresponding preset parameters can be called according to the names of the feature information to perform judgment.
S240, determining the characteristic information that the monitoring parameters do not meet the corresponding preset parameters as target characteristic information.
The target feature information refers to feature information, among a plurality of feature information, of which the monitoring parameters do not meet corresponding preset parameters. For example, when the feature information is occupational, the corresponding preset duty ratio is 3%; when the characteristic information is sex, the corresponding preset duty ratio is 20%. If the monitoring parameter of the occupation is 5%, the characteristic information of the occupation is target characteristic information; if the monitored parameter of the sex is 10%, the characteristic information of the sex is not the target characteristic information.
S250, alarming and prompting the target characteristic information.
In the step, the target characteristic information is subjected to alarm prompt, and the alarm prompt can be performed in a targeted manner, so that unified alarm prompt is avoided, and the abnormal specific characteristic information is analyzed.
According to the technical scheme, the characteristic data set of the user is obtained, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information. By judging the monitoring parameters of the characteristic information, the problem investigation is avoided when the recommended effect is not good, and the monitoring parameters of the characteristic information can be timely judged to determine whether to alarm or not, so that the technical effect of timely monitoring and alarming the data is achieved.
Example III
Fig. 3 is a schematic structural diagram of a data monitoring and alarming device according to a third embodiment of the present invention, where the present embodiment is applicable to a scenario of monitoring and alarming feature data for commodity recommendation, and the device may be implemented in a software and/or hardware manner and may be integrated on a server.
As shown in fig. 3, the data monitoring alarm apparatus provided in this embodiment may include a feature data set acquisition module 310, a monitoring parameter determination module 320, a judgment module 330, and an alarm prompting module 340, where:
a feature data set obtaining module 310, configured to obtain a feature data set of a user, where the feature data set includes feature information of the user and initial parameters corresponding to the feature information; the monitoring parameter determining module 320 is configured to determine a monitoring parameter corresponding to the feature information according to an initial parameter corresponding to the feature information; a judging module 330, configured to judge whether the monitored parameter meets a preset parameter; and the alarm prompting module 340 is configured to issue an alarm prompt for abnormality of the feature information when the monitored parameter does not meet the preset parameter.
Optionally, the feature data set acquisition module 310 includes: a monitoring unit, configured to monitor a message queue, where the message queue is configured to receive the feature data set from a recommendation system; and the characteristic data set acquisition unit is used for extracting the characteristic data set from the message queue when the message queue is monitored to be updated.
Optionally, the monitoring parameter determining module 320 is specifically configured to extract an initial parameter corresponding to the feature information from the feature data set, so as to determine the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information.
Optionally, the feature information is multiple, and the monitoring parameter determining module 320 is specifically configured to determine a monitoring parameter corresponding to each feature information according to an initial parameter of each feature information; the judging module 330 is specifically configured to judge whether the monitoring parameter corresponding to each feature information meets a corresponding preset parameter; the alarm prompting module 340 is specifically configured to determine, as target feature information, feature information that the monitored parameter does not meet the corresponding preset parameter; and carrying out alarm prompt on the target characteristic information.
Optionally, the monitoring parameter determining module 320 includes: the storage unit is used for storing initial parameters corresponding to the characteristic information into a distributed document database; the judging unit is used for judging whether the current time reaches a first preset time or not; an initial parameter calling unit, configured to call, from the distributed document database, an initial parameter corresponding to the feature information when the current time reaches the first preset time; and the calculating unit is used for calculating the initial parameters corresponding to the characteristic information so as to determine the monitoring parameters corresponding to the characteristic information.
Optionally, the monitoring parameter includes average response time consumption, duty ratio and/or request exception duty ratio, and the judging module 330 is specifically configured to judge whether the average response time consumption, duty ratio and/or request exception duty ratio meet preset parameters corresponding to the average response time consumption, duty ratio and/or request exception duty ratio; the alarm prompting module 340 is specifically configured to issue an alarm prompt for the characteristic information abnormality when the average response time consumption, the duty ratio and/or the request abnormality ratio do not satisfy the preset parameters corresponding to the average response time consumption, the duty ratio and/or the request abnormality ratio.
Optionally, the judging module 330 includes: a preset configuration table calling unit, configured to call a preset configuration table from a preset database, where the preset configuration table carries the preset parameters; and the monitoring parameter judging unit is used for judging whether the monitoring parameter meets the preset parameter of the preset configuration table.
The data monitoring and alarming device provided by the embodiment of the invention can execute the data monitoring and alarming method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Reference may be made to the description of any method embodiment of the invention for details not explicitly described in this embodiment of the invention.
Example IV
Fig. 4 is a schematic structural diagram of a server according to a fourth embodiment of the present invention. Fig. 4 illustrates a block diagram of an exemplary server 612 suitable for use in implementing embodiments of the invention. The server 612 depicted in fig. 4 is merely an example, and is not meant to limit the functionality and scope of use of embodiments of the present invention.
As shown in fig. 4, the server 612 is in the form of a general-purpose server. Components of server 612 may include, but are not limited to: one or more processors 616, a memory device 628, and a bus 618 that connects the various system components, including the memory device 628 and the processor 616.
Bus 618 represents one or more of several types of bus structures, including a memory device bus or memory device controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry standard architecture (Industry Subversive Alliance, ISA) bus, micro channel architecture (Micro Channel Architecture, MAC) bus, enhanced ISA bus, video electronics standards association (Video Electronics Standards Association, VESA) local bus, and peripheral component interconnect (Peripheral Component Interconnect, PCI) bus.
Server 612 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by server 612 and includes both volatile and nonvolatile media, removable and non-removable media.
The storage 628 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory, RAM) 630 and/or cache memory 632. The server 612 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 634 can be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, commonly referred to as a "hard drive"). Although not shown in fig. 4, a magnetic disk drive for reading from and writing to a removable nonvolatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable nonvolatile optical disk such as a Read Only Memory (CD-ROM), digital versatile disk (Digital Video Disc-Read Only Memory, DVD-ROM), or other optical media, may be provided. In such cases, each drive may be coupled to bus 618 through one or more data medium interfaces. The storage 628 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the present invention.
A program/utility 640 having a set (at least one) of program modules 642 may be stored, for example, in the storage 628, such program modules 642 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 642 generally perform the functions and/or methods of the described embodiments of the present invention.
The server 612 may also communicate with one or more external devices 614 (e.g., keyboard, pointing terminal, display 624, etc.), with one or more terminals that enable a user to interact with the server 612, and/or with any terminal (e.g., network card, modem, etc.) that enables the server 612 to communicate with one or more other computing terminals. Such communication may occur through an input/output (I/O) interface 622. Also, the server 612 may communicate with one or more networks (e.g., local area network (Local Area Network, LAN), wide area network (Wide Area Network, WAN) and/or public network, such as the internet) via the network adapter 620. As shown in fig. 4, network adapter 620 communicates with the other modules of server 612 over bus 618. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with server 612, including, but not limited to: microcode, end drives, redundant processors, external disk drive arrays, disk array (Redundant Arrays of Independent Disks, RAID) systems, tape drives, data backup storage systems, and the like.
The processor 616 executes various functional applications and data processing by running programs stored in the storage 628, such as implementing a data monitoring alarm method provided by any embodiment of the present invention, the method may include:
acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information;
determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
judging whether the monitoring parameters meet preset parameters or not;
and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information.
According to the technical scheme, the characteristic data set of the user is obtained, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information. By judging the monitoring parameters of the characteristic information, the problem investigation is avoided when the recommended effect is not good, and the monitoring parameters of the characteristic information can be timely judged to determine whether to alarm or not, so that the technical effect of timely monitoring and alarming the data is achieved.
Example five
The fifth embodiment of the present invention further provides a computer readable storage medium having a computer program stored thereon, where the program when executed by a processor implements a data monitoring and alarming method as provided in any embodiment of the present invention, the method may include:
acquiring a characteristic data set of a user, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information;
determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
judging whether the monitoring parameters meet preset parameters or not;
and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information.
The computer-readable storage media of embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or terminal. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
According to the technical scheme, the characteristic data set of the user is obtained, wherein the characteristic data set comprises characteristic information of the user and initial parameters corresponding to the characteristic information; determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information; judging whether the monitoring parameters meet preset parameters or not; and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information. By judging the monitoring parameters of the characteristic information, the problem investigation is avoided when the recommended effect is not good, and the monitoring parameters of the characteristic information can be timely judged to determine whether to alarm or not, so that the technical effect of timely monitoring and alarming the data is achieved.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (7)
1. A data monitoring and alerting method, the method comprising:
a listening message queue for receiving a feature dataset from a recommender system;
extracting the feature data set from the message queue when the message queue update is monitored; the characteristic data set comprises characteristic information of a user and initial parameters corresponding to the characteristic information;
determining monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
judging whether the monitoring parameters meet preset parameters or not;
when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormality of the characteristic information;
when the characteristic data set comprises characteristic information of the same user and initial parameters of the characteristic information, the monitoring parameters comprise time consumption for acquiring the characteristic information of the user, whether the characteristic information of the user is empty or not and whether a request for acquiring the characteristic information of the user is successful or not; when the feature data set comprises the same feature information of different users and a plurality of initial parameters of the same feature information, the monitoring parameters comprise average response time consumption, null value duty ratio and request abnormality duty ratio;
correspondingly, the judging whether the monitoring parameter meets the preset parameter or not, and when the monitoring parameter does not meet the preset parameter, sending out the alarm prompt of the abnormal characteristic information comprises the following steps:
judging whether the average response time consumption, the duty ratio and the request abnormality duty ratio meet preset parameters corresponding to the average response time consumption, the duty ratio and the request abnormality duty ratio or not;
when the average response time consumption, the duty ratio and the request abnormality duty ratio do not meet preset parameters corresponding to the average response time consumption, the duty ratio and the request abnormality duty ratio, an alarm prompt of the characteristic information abnormality is sent; wherein the request abnormal duty ratio is the ratio of the number of failed request to acquire the characteristic data set of the user to the total number of requests to acquire the characteristic data set;
wherein, the determining the monitoring parameter corresponding to the characteristic information according to the initial parameter corresponding to the characteristic information includes:
storing initial parameters corresponding to the characteristic information into a distributed document database;
judging whether the current time reaches a first preset time or not; the first preset time refers to time for judging whether to call the initial parameter to calculate the monitoring parameter, and is obtained by adding a preset time period to time for calculating the monitoring parameter last time;
when the current time reaches the first preset time, calling initial parameters corresponding to the characteristic information from the distributed document database;
and calculating initial parameters corresponding to the characteristic information to determine monitoring parameters corresponding to the characteristic information.
2. The data monitoring and alarming method of claim 1, wherein the determining the monitoring parameter corresponding to the characteristic information according to the initial parameter corresponding to the characteristic information comprises:
extracting initial parameters corresponding to the characteristic information from the characteristic data set, so as to determine monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information.
3. The data monitoring and alarming method of claim 1, wherein the feature information is a plurality of, and the determining the monitoring parameter corresponding to the feature information according to the initial parameter corresponding to the feature information includes:
determining a monitoring parameter corresponding to each piece of characteristic information according to the initial parameter of each piece of characteristic information;
judging whether the monitoring parameters meet preset parameters or not, and when the monitoring parameters do not meet the preset parameters, sending out an alarm prompt of abnormal characteristic information comprises the following steps:
judging whether the monitoring parameters corresponding to each piece of characteristic information meet the corresponding preset parameters or not;
determining the characteristic information that the monitoring parameters do not meet the corresponding preset parameters as target characteristic information;
and carrying out alarm prompt on the target characteristic information.
4. The data monitoring alarm method of claim 1 wherein said determining whether said monitored parameter meets a preset parameter comprises:
calling a preset configuration table from a preset database, wherein the preset configuration table carries the preset parameters;
and judging whether the monitoring parameters meet preset parameters of the preset configuration table or not.
5. A data monitoring and alert device, the device comprising:
the device comprises a feature data set acquisition module, a feature data set acquisition module and a feature data processing module, wherein the feature data set is used for acquiring a feature data set of a user, and comprises feature information of the user and initial parameters corresponding to the feature information;
the monitoring parameter determining module is used for determining the monitoring parameters corresponding to the characteristic information according to the initial parameters corresponding to the characteristic information;
the judging module is used for judging whether the monitoring parameters meet preset parameters or not;
the alarm prompting module is used for sending out an alarm prompt of abnormal characteristic information when the monitoring parameters do not meet the preset parameters;
wherein, the characteristic data set acquisition module includes:
a monitoring unit, configured to monitor a message queue, where the message queue is configured to receive the feature data set from a recommendation system;
a feature data set acquisition unit configured to extract the feature data set from the message queue when the message queue update is monitored;
when the characteristic data set comprises characteristic information of the same user and initial parameters of the characteristic information, the monitoring parameters comprise time consumption for acquiring the characteristic information of the user, whether the characteristic information of the user is empty or not and whether a request for acquiring the characteristic information of the user is successful or not; when the feature data set comprises the same feature information of different users and a plurality of initial parameters of the same feature information, the monitoring parameters comprise average response time consumption, null value duty ratio and request abnormality duty ratio; said determining whether said monitored parameters meet preset parameters,
correspondingly, the judging module is specifically configured to judge whether the average response time consumption, the duty ratio and the request exception duty ratio meet preset parameters corresponding to the average response time consumption, the duty ratio and the request exception duty ratio;
the alarm prompting module is specifically configured to send an alarm prompt for the characteristic information abnormality when the average response time consumption, the duty ratio and the request abnormality ratio do not meet preset parameters corresponding to the average response time consumption, the duty ratio and the request abnormality ratio; wherein the request abnormal duty ratio is the ratio of the number of failed request to acquire the characteristic data set of the user to the total number of requests to acquire the characteristic data set;
wherein, the monitoring parameter determining module comprises:
the storage unit is used for storing initial parameters corresponding to the characteristic information into a distributed document database;
the judging unit is used for judging whether the current time reaches a first preset time or not; the first preset time refers to time for judging whether to call the initial parameter to calculate the monitoring parameter, and is obtained by adding a preset time period to time for calculating the monitoring parameter last time;
an initial parameter calling unit, configured to call, from the distributed document database, an initial parameter corresponding to the feature information when the current time reaches the first preset time;
and the calculating unit is used for calculating the initial parameters corresponding to the characteristic information so as to determine the monitoring parameters corresponding to the characteristic information.
6. A server, comprising:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data monitoring alert method of any of claims 1-4.
7. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements a data monitoring alarm method as claimed in any of claims 1-4.
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